Technical Field
The present invention relates to a method and system for automatically optimizing point cloud data quality.
Related Art
Three-dimensional modeling is a hot issue in the field of computer science. Its modeling method is divided into two categories according to data sources: a modeling method based on three-dimensional scattered point and a modeling method based on images (single-frame, multi-frame, sequence). A three-dimensional laser scanning system can rapidly acquire three-dimensional positions and geometric texture information on surfaces of a target object, and is widely used in the field of three-dimensional modeling as data acquired has relatively high precision. However, most of the existing modeling methods obtain original point cloud data required by modeling by scanning a target through a specific scanning instrument, and then, in a late offline state, use a series of artificially designed precision optimization algorithms to process, such as splice, denoise, simplify, feature-extract and fuse, the acquired point cloud data, so as to obtain a high-precision three-dimensional model. Here, one key factor having a significant impact on modeling precision is measurement precision of a scanner that initially acquires data.
Most of the existing three-dimensional modeling technologies are applied to point cloud data with higher relative quality that has been pre-processed. That is, acquired discrete point clouds undergo certain artificial cleaning and filling offline, and then the discrete point clouds are calculated into a mesh model by using an artificially designed optimization algorithm which has high requirements for regularity of input data, i.e., a method based on computation geometry or a method based on implicit surface, plus certain texturing and rendering, to finally achieve the purpose of three-dimensional modeling. Thus, most of the existing high-precision three-dimensional modeling technologies heavily rely on measurement precision of hardware devices, and also require more artificial participation.